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Journal of Bioinformatics and Computational Biology

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https://www.readbyqxmd.com/read/29945503/proposing-drug-fragments-for-dengue-virus-ns5-protein
#1
Amr Alhossary, Yaw Awuni, Chee Keong Kwoh, Yuguang Mu
Dengue fever is a febrile illness caused by Dengue Virus, which belongs to the Flaviviridae family. Among its proteome, the nonstructural protein 5 (NS5) is the biggest and most conserved. It has a primer-independent RNA-dependent RNA polymerase (RdRp) domain at its C-Terminus. Zou et al. studied the biological relevance of the two conserved cavities (named A and B) within the NS5 proteins of dengue virus (DENV) and West Nile Virus (WNV) using mutagenesis and revertant analysis and found four mutations located at cavity B having effects on viral replication...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29945502/compound-property-enhancement-by-virtual-compound-synthesis
#2
Naoki Arai, Shunsuke Yoshikawa, Nobuaki Yasuo, Ryunosuke Yoshino, Masakazu Sekijima
During drug discovery, drug candidates are narrowed down over several steps to develop pharmaceutical products. The theoretical chemical space in such steps is estimated to be [Formula: see text]. To cover that space, extensive virtual compound libraries have been developed; however, the compilation of extensive libraries comes at large computational cost. Thus, to reduce the computational cost, researchers have constructed custom-made virtual compound libraries that focus on target diseases. In this study, we develop a system that generates virtual compound libraries from input compounds...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29945501/introduction-to-selected-papers-from-giw2017
#3
Lee Sael
No abstract text is available yet for this article.
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29945500/investigation-of-non-hydroxamate-scaffolds-against-hdac6-inhibition-a-pharmacophore-modeling-molecular-docking-and-molecular-dynamics-simulation-approach
#4
Amir Zeb, Chanin Park, Minky Son, Shailima Rampogu, Syed Ibrar Alam, Seok Ju Park, Keun Woo Lee
Proteins deacetylation by Histone deacetylase 6 (HDAC6) has been shown in various human chronic diseases like neurodegenerative diseases and cancer, and hence is an important therapeutic target. Since, the existing inhibitors have hydroxamate group, and are not HDAC6-selective, therefore, this study has designed to investigate non-hydroxamate HDAC6 inhibitors. Ligand-based pharmacophore was generated from 26 training set compounds of HDAC6 inhibitors. The statistical parameters of pharmacophore (Hypo1) included lowest total cost of 115...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29945499/a-transfer-learning-approach-via-procrustes-analysis-and-mean-shift-for-cancer-drug-sensitivity-prediction
#5
Turki Turki, Zhi Wei, Jason T L Wang
Transfer learning (TL) algorithms aim to improve the prediction performance in a target task (e.g. the prediction of cisplatin sensitivity in triple-negative breast cancer patients) via transferring knowledge from auxiliary data of a related task (e.g. the prediction of docetaxel sensitivity in breast cancer patients), where the distribution and even the feature space of the data pertaining to the tasks can be different. In real-world applications, we sometimes have a limited training set in a target task while we have auxiliary data from a related task...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29792377/comparative-analysis-of-probiotic-bacteria-based-on-a-new-definition-of-core-genome
#6
Maria Satti, Yasuhiro Tanizawa, Akihito Endo, Masanori Arita
The commensal genus Bifidobacterium has probiotic properties. We prepared a public library of the gene functions of the genus Bifidobacterium for its online annotation. Orthologous gene cluster analysis showed that the pan genomes of Bifidobacterium and Lactobacillus exhibit striking similarities when mapped to the Clusters of Orthologous Group (COG) database of proteins. When the core genes in each genus were selected based on our statistical definition of "core genome", core genes were present in at least 92% of 52 Bifidobacterium and in 97% of 178 Lactobacillus genomes...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29591488/prediction-of-microrna-binding-residues-in-protein-using-a-laplacian-support-vector-machine-based-on-sequence-information
#7
Xin Ma, Jing Guo, Xiao Sun
The identification of microRNA (miRNA)-binding protein residues significantly impacts several research areas, including gene regulation and expression. We propose a method, PmiRBR, which combines a novel hybrid feature with the Laplacian support vector machine (LapSVM) algorithm to predict miRNA-binding residues in protein sequences. The hybrid feature is constituted by secondary structure, conservation scores, and a novel feature, which includes evolutionary information combined with the physicochemical properties of amino acids...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29566638/gi-cluster-detecting-genomic-islands-via-consensus-clustering-on-multiple-features
#8
Bingxin Lu, Hon Wai Leong
The accurate detection of genomic islands (GIs) in microbial genomes is important for both evolutionary study and medical research, because GIs may promote genome evolution and contain genes involved in pathogenesis. Various computational methods have been developed to predict GIs over the years. However, most of them cannot make full use of GI-associated features to achieve desirable performance. Additionally, many methods cannot be directly applied to newly sequenced genomes. We develop a new method called GI-Cluster, which provides an effective way to integrate multiple GI-related features via consensus clustering...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29566637/integrating-virtual-screening-and-biochemical-experimental-approach-to-identify-potential-anti-cancer-agents-from-drug-databank
#9
Suman Jyoti Deka, Ashalata Roy, Debasis Manna, Vishal Trivedi
Chemical libraries constitute a reservoir of pharmacophoric molecules to identify potent anti-cancer agents. Virtual screening of heterocyclic compound library in conjugation with the agonist-competition assay, toxicity-carcinogenicity analysis, and string-based structural searches enabled us to identify several drugs as potential anti-cancer agents targeting protein kinase C (PKC) as a target. Molecular modeling study indicates that Cinnarizine fits well within the PKC C2 domain and exhibits extensive interaction with the protein residues...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29566636/an-automated-approach-to-classification-of-duplex-assay-for-digital-droplet-pcr
#10
Cong Liu, Wuping Zhou, Tao Zhang, Keming Jiang, Haiwen Li, Wenfei Dong
In the digital polymerase chain reaction (dPCR) detection process, discriminating positive droplets from negative ones directly affects the final concentration and is one of the most important factors affecting accuracy. Current automated classification methods usually discuss single-channel detections, whereas duplex detection experiments are less discussed. In this paper, we designed a classification method by estimating the upper limit of the negative droplets. The right tail of the negative droplets is approximated using a generalized Pareto distribution...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29478376/rppaware-a-software-suite-to-preprocess-analyze-and-visualize-reverse-phase-protein-array-data
#11
A Ranjitha Dhanasekaran, Katheleen J Gardiner
Reverse Phase Protein Arrays (RPPA) is a high-throughput technology used to profile levels of protein expression. Handling the large datasets generated by RPPA can be facilitated by appropriate software tools. Here, we describe RPPAware, a free and intuitive software suite that was developed specifically for analysis and visualization of RPPA data. RPPAware is a portable tool that requires no installation and was built using Java. Many modules of the tool invoke R to utilize the statistical features. To demonstrate the utility of RPPAware, data generated from screening brain regions of a mouse model of Down syndrome with 62 antibodies were used as a case study...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29347875/universal-informative-cpg-sites-for-inferring-tumor-purity-from-dna-methylation-microarray-data
#12
Haixia Dou, Yun Fang, Xiaoqi Zheng
Tumor purity is an intrinsic property of tumor samples and potentially has severe impact on many types of data analysis. We have previously developed a statistical method, InfiniumPurify, which could infer purity of a tumor sample given its tumor type (available in TCGA) or a set of informative CpG (iDMC) sites. However, in many clinical practices, researchers may focus on a specific type of tumor samples that is not included in TCGA, and samples which are too few to identify reliable iDMCs. This greatly restricts the application of InfiniumPurify in cancer research...
June 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/30105928/a-hybrid-solver-for-protein-multiple-sequence-alignment-problem
#13
Lamiche Chaabane
In this work, a novel hybrid model called PSOSA for solving multiple sequence alignment (MSA) problem is proposed. The developed approach is a combination between particle swarm optimization (PSO) algorithm and simulated annealing (SA) technique. In our PSOSA approach, PSO is exploited in global search, but it is easily trapped into local optimum and may lead to premature convergence. SA is incorporated as local improvement approach to overcome local optimum problem and intensify the search in local regions to improve solution quality...
May 29, 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/30105927/computational-prediction-of-antifungal-peptides-via-chou-s-pseaac-and-svm
#14
Maryam Mousavizadegan, Hassan Mohabatkar
With the increase in immunocompromised patients in the recent years, fungal infections have emerged as new and serious threat in hospitals. This, and the insufficiency of current antifungal therapies alongside their toxic effects on patients, has led to the increased interest in seeking new antifungal peptides. In the present study, we have developed a prediction method for screening of antifungal peptides. For this, we have chosen Chou's pseudo amino acid composition (PseAAC) to translate peptide sequences into numeric values...
May 29, 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/30060698/training-host-pathogen-protein-protein-interaction-predictors
#15
Abdul Hannan Basit, Wajid Arshad Abbasi, Amina Asif, Sadaf Gull, Fayyaz Ul Amir Afsar Minhas
Detection of protein-protein interactions (PPIs) plays a vital role in molecular biology. Particularly, pathogenic infections are caused by interactions of host and pathogen proteins. It is important to identify host-pathogen interactions (HPIs) to discover new drugs to counter infectious diseases. Conventional wet lab PPI detection techniques have limitations in terms of cost and large-scale application. Hence, computational approaches are developed to predict PPIs. This study aims to develop machine learning models to predict inter-species PPIs with a special interest in HPIs...
May 29, 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/30012015/accurate-prediction-of-human-mirna-targets-via-graph-modeling-of-the-mirna-target-duplex
#16
Mohammad Mohebbi, Liang Ding, Russell L Malmberg, Cory Momany, Khaled Rasheed, Liming Cai
miRNAs are involved in many critical cellular activities through binding to their mRNA targets, e.g. in cell proliferation, differentiation, death, growth control, and developmental timing. Accurate prediction of miRNA targets can assist efficient experimental investigations on the functional roles of miRNAs. Their prediction, however, remains a challengeable task due to the lack of experimental data about the tertiary structure of miRNA-target binding duplexes. In particular, correlations of nucleotides in the binding duplexes may not be limited to the canonical Watson Crick base pairs (BPs) as they have been perceived; methods based on secondary structure prediction (typically minimum free energy (MFE)) have only had mix success...
May 7, 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/30051743/modeling-the-probability-distribution-of-the-bacterial-burst-size-via-a-game-theoretic-approach
#17
Seyed Amir Malekpour, Parsa Pakzad, Mohammad-Hadi Foroughmand-Araabi, Sama Goliaei, Ruzbeh Tusserkani, Bahram Goliaei, Mehdi Sadeghi
Based on previous studies, empirical distribution of the bacterial burst size varies even in a population of isogenic bacteria. Since bacteriophage progenies increase linearly with time, it is the lysis time variation that results in the bacterial burst size variations. Here, the burst size variation is computationally modeled by considering the lysis time decisions as a game. Each player in the game is a bacteriophage that has initially infected and lysed its host bacterium. Also, the payoff of each burst size strategy is the average number of bacteria that are solely infected by the bacteriophage progenies after lysis...
May 3, 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/30051742/inference-of-gene-networks-from-gene-expression-time-series-using-recurrent-neural-networks-and-sparse-map-estimation
#18
Chi-Kan Chen
Background The inference of genetic regulatory networks (GRNs) provides insight into the cellular responses to signals. A class of recurrent neural networks (RNNs) capturing the dynamics of GRN has been used as a basis for inferring small-scale GRNs from gene expression time series. The Bayesian framework facilitates incorporating the hypothesis of GRN into the model estimation to improve the accuracy of GRN inference. Results We present new methods for inferring small-scale GRNs based on RNNs. The weights of wires of RNN represent the strengths of gene-to-gene regulatory interactions...
April 26, 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29954288/succinate-aggravates-nafld-progression-to-liver-cancer-on-the-onset-of-obesity-an-in-silico-model
#19
Indrani Ray, Abhijit Dasgupta, Rajat K De
The incidence and prevalence of nonalcoholic fatty liver disease (NAFLD) have been increasing to epidemic proportions around the world. NAFLD, a chronic liver disease that affects the nondrinkers, is mainly associated with steatohepatitis and cirrhosis. The progression of NAFLD associated with obesity increases the risk of liver cancer, a disease with poor outcomes and limited therapeutic options. In order to investigate the underlying cellular dynamics leading to NAFLD progression towards cancer on the onset of obesity, we have integrated human hepatocyte pathway with hypoxia-inducible factor1-[Formula: see text] (HIF1-[Formula: see text]) signaling pathway using state space model based on classical control theory...
April 26, 2018: Journal of Bioinformatics and Computational Biology
https://www.readbyqxmd.com/read/29954287/new-variable-selection-strategy-for-analysis-of-high-dimensional-dna-methylation-data
#20
Jiyun Choi, Kipoong Kim, Hokeun Sun
In genetic association studies, regularization methods are often used due to their computational efficiency for analysis of high-dimensional genomic data. DNA methylation data generated from Infinium HumanMethylation450 BeadChip Kit have a group structure where an individual gene consists of multiple Cytosine-phosphate-Guanine (CpG) sites. Consequently, group-based regularization can precisely detect outcome-related CpG sites. Representative examples are sparse group lasso (SGL) and network-based regularization...
April 26, 2018: Journal of Bioinformatics and Computational Biology
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